A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit and 4-bit floating point (FP8 and FP4) precision on Hopper, Ada and Blackwell GPUs, to provide better performance…

The best ChatGPT that $100 can buy.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

大模型基础: 一文了解大模型基础知识

Minimalist developer portfolio using Next.js 14, React, TailwindCSS, Shadcn UI and Magic UI

Material for gpu-mode lectures

how to optimize some algorithm in cuda.

Democratizing Reinforcement Learning for LLMs

Search-R1: An Efficient, Scalable RL Training Framework for Reasoning & Search Engine Calling interleaved LLM based on veRL

This is the homepage of a new book entitled "Mathematical Foundations of Reinforcement Learning."

🐶 Kubernetes CLI To Manage Your Clusters In Style!

Ongoing research training transformer models at scale

slime is an LLM post-training framework for RL Scaling.

A Survey of Reinforcement Learning for Large Reasoning Models

Lightning-Fast RL for LLM Reasoning and Agents. Made Simple & Flexible.

KernelBench: Can LLMs Write GPU Kernels? - Benchmark + Toolkit with Torch -> CUDA (+ more DSLs)

Fast and memory-efficient exact attention

gpt-oss-120b and gpt-oss-20b are two open-weight language models by OpenAI

A unified library of SOTA model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. It compresses deep learning models for downstream deployment frameworks …

SOTA low-bit LLM quantization (INT8/FP8/MXFP8/INT4/MXFP4/NVFP4) & sparsity; leading model compression techniques on PyTorch, TensorFlow, and ONNX Runtime

A streamlined and customizable framework for efficient large model (LLM, VLM, AIGC) evaluation and performance benchmarking.

Transformers-compatible library for applying various compression algorithms to LLMs for optimized deployment with vLLM

[MLSys'25] QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving; [MLSys'25] LServe: Efficient Long-sequence LLM Serving with Unified Sparse Attention

A framework for few-shot evaluation of language models.

PyTorch native quantization and sparsity for training and inference

AIInfra（AI 基础设施）指AI系统从底层芯片等硬件，到上层软件栈支持AI大模型训练和推理。

AISystem 主要是指AI系统，包括AI芯片、AI编译器、AI推理和训练框架等AI全栈底层技术

A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training

The simplest, fastest repository for training/finetuning medium-sized GPTs.